Examples with DepthChoiceGenerator edu.cmu.tetrad.util.DepthChoiceGenerator used on opensource projects

Example 11 with DepthChoiceGenerator

use of edu.cmu.tetrad.util.DepthChoiceGenerator in project tetrad by cmu-phil.

the class Mbfs method search.

/**
 * Searches for the MB Pattern for the given target.
 *
 * @param target The target variable.
 */
public Graph search(Node target) {
    long start = System.currentTimeMillis();
    this.numIndependenceTests = 0;
    this.allTriples = new HashSet<>();
    this.ambiguousTriples = new HashSet<>();
    this.colliderTriples = new HashSet<>();
    this.noncolliderTriples = new HashSet<>();
    if (target == null) {
        throw new IllegalArgumentException("Null target name not permitted");
    }
    this.target = target;
    logger.log("info", "Target = " + target);
    // Some statistics.
    this.maxRemainingAtDepth = new int[20];
    this.maxVariableAtDepth = new Node[20];
    Arrays.fill(maxRemainingAtDepth, -1);
    Arrays.fill(maxVariableAtDepth, null);
    logger.log("info", "target = " + getTarget());
    Graph graph = new EdgeListGraph();
    // Each time the addDepthZeroAssociates method is called for a node
    // v, v is added to this set, and edges to elements in this set are
    // not added to the graph subsequently. This is to handle the situation
    // of adding v1---v2 to the graph, removing it by conditioning on
    // nodes adjacent to v1, then re-adding it and not being able to
    // remove it by conditioning on nodes adjacent to v2. Once an edge
    // is removed, it should not be re-added to the graph.
    // jdramsey 8/6/04
    this.a = new HashSet<>();
    // Step 1. Get associates for the target.
    logger.log("info", "BEGINNING step 1 (prune target).");
    graph.addNode(getTarget());
    constructFan(getTarget(), graph);
    logger.log("graph", "After step 1 (prune target)" + graph);
    logger.log("graph", "After step 1 (prune target)" + graph);
    // Step 2. Get associates for each variable adjacent to the target,
    // removing edges based on those associates where possible. After this
    // step, adjacencies to the target are parents or children of the target.
    // Call this set PC.
    logger.log("info", "BEGINNING step 2 (prune PC).");
    for (Node v : graph.getAdjacentNodes(getTarget())) {
        if (Thread.currentThread().isInterrupted()) {
            break;
        }
        constructFan(v, graph);
        W: for (Node w : graph.getAdjacentNodes(v)) {
            if (Thread.currentThread().isInterrupted()) {
                break;
            }
            if (a.contains(w)) {
                continue;
            }
            List _a = new LinkedList<>(a);
            _a.retainAll(graph.getAdjacentNodes(w));
            if (_a.size() > 1)
                continue;
            List<Node> adjT = graph.getAdjacentNodes(getTarget());
            DepthChoiceGenerator cg = new DepthChoiceGenerator(adjT.size(), depth);
            int[] choice;
            while ((choice = cg.next()) != null) {
                if (Thread.currentThread().isInterrupted()) {
                    break;
                }
                List<Node> s = GraphUtils.asList(choice, adjT);
                if (!s.contains(v))
                    continue;
                if (independent(getTarget(), w, s)) {
                    graph.removeEdge(v, w);
                    continue W;
                }
            }
        }
    }
    logger.log("graph", "After step 2 (prune PC)" + graph);
    // Step 3. Get associates for each node now two links away from the
    // target, removing edges based on those associates where possible.
    // After this step, adjacencies to adjacencies of the target are parents
    // or children of adjacencies to the target. Call this set PCPC.
    logger.log("info", "BEGINNING step 3 (prune PCPC).");
    for (Node v : graph.getAdjacentNodes(getTarget())) {
        for (Node w : graph.getAdjacentNodes(v)) {
            if (getA().contains(w)) {
                continue;
            }
            constructFan(w, graph);
        }
    }
    logger.log("graph", "After step 3 (prune PCPC)" + graph);
    logger.log("info", "BEGINNING step 4 (PC Orient).");
    SearchGraphUtils.pcOrientbk(knowledge, graph, graph.getNodes());
    List<Node> _visited = new LinkedList<>(getA());
    orientUnshieldedTriples(knowledge, graph, getTest(), getDepth(), _visited);
    MeekRules meekRules = new MeekRules();
    meekRules.setAggressivelyPreventCycles(this.aggressivelyPreventCycles);
    meekRules.setKnowledge(knowledge);
    meekRules.orientImplied(graph);
    logger.log("graph", "After step 4 (PC Orient)" + graph);
    logger.log("info", "BEGINNING step 5 (Trim graph to {T} U PC U " + "{Parents(Children(T))}).");
    MbUtils.trimToMbNodes(graph, getTarget(), false);
    logger.log("graph", "After step 5 (Trim graph to {T} U PC U {Parents(Children(T))})" + graph);
    logger.log("info", "BEGINNING step 6 (Remove edges among P and P of C).");
    MbUtils.trimEdgesAmongParents(graph, getTarget());
    MbUtils.trimEdgesAmongParentsOfChildren(graph, getTarget());
    logger.log("graph", "After step 6 (Remove edges among P and P of C)" + graph);
    // logger.log("details", "Bounds: ");
    // 
    // for (int i = 0; i < maxRemainingAtDepth.length; i++) {
    // if (maxRemainingAtDepth[i] != -1) {
    // logger.log("details", "\ta" + i + " = " + maxRemainingAtDepth[i] +
    // " (" + maxVariableAtDepth[i] + ")");
    // }
    // }
    // System.out.println("Number of fan constructions = " + visited.size());
    finishUp(start, graph);
    this.logger.log("graph", "\nReturning this graph: " + graph);
    this.graph = graph;
    return graph;
}

Example 12 with DepthChoiceGenerator

use of edu.cmu.tetrad.util.DepthChoiceGenerator in project tetrad by cmu-phil.

the class SemBicScore method printMinimalLinearlyDependentSet.

// Prints a smallest subset of parents that causes a singular matrix exception.
private boolean printMinimalLinearlyDependentSet(int[] parents, ICovarianceMatrix cov) {
    List<Node> _parents = new ArrayList<>();
    for (int p : parents) _parents.add(variables.get(p));
    DepthChoiceGenerator gen = new DepthChoiceGenerator(_parents.size(), _parents.size());
    int[] choice;
    while ((choice = gen.next()) != null) {
        int[] sel = new int[choice.length];
        List<Node> _sel = new ArrayList<>();
        for (int m = 0; m < choice.length; m++) {
            sel[m] = parents[m];
            _sel.add(variables.get(sel[m]));
        }
        TetradMatrix m = cov.getSelection(sel, sel);
        try {
            m.inverse();
        } catch (Exception e2) {
            forbidden.add(sel[0]);
            out.println("### Linear dependence among variables: " + _sel);
            out.println("### Removing " + _sel.get(0));
            return true;
        }
    }
    return false;
}

Example 13 with DepthChoiceGenerator

use of edu.cmu.tetrad.util.DepthChoiceGenerator in project tetrad by cmu-phil.

the class MixedBicScore method printMinimalLinearlyDependentSet.

// Prints a smallest subset of parents that causes a singular matrix exception.
private boolean printMinimalLinearlyDependentSet(int[] parents, ICovarianceMatrix cov) {
    List<Node> _parents = new ArrayList<>();
    for (int p : parents) _parents.add(variables.get(p));
    DepthChoiceGenerator gen = new DepthChoiceGenerator(_parents.size(), _parents.size());
    int[] choice;
    while ((choice = gen.next()) != null) {
        int[] sel = new int[choice.length];
        List<Node> _sel = new ArrayList<>();
        for (int m = 0; m < choice.length; m++) {
            sel[m] = parents[m];
            _sel.add(variables.get(sel[m]));
        }
        TetradMatrix m = cov.getSelection(sel, sel);
        try {
            m.inverse();
        } catch (Exception e2) {
            forbidden.add(sel[0]);
            out.println("### Linear dependence among variables: " + _sel);
            out.println("### Removing " + _sel.get(0));
            return true;
        }
    }
    return false;
}

Example 14 with DepthChoiceGenerator

use of edu.cmu.tetrad.util.DepthChoiceGenerator in project tetrad by cmu-phil.

the class OrientCollidersMaxP method testColliderMaxP.

private void testColliderMaxP(Graph graph, Map<Triple, Double> scores, Node a, Node b, Node c) {
    List<Node> adja = graph.getAdjacentNodes(a);
    List<Node> adjc = graph.getAdjacentNodes(c);
    adja.remove(c);
    adjc.remove(a);
    double score = Double.POSITIVE_INFINITY;
    List<Node> S = null;
    DepthChoiceGenerator cg1 = new DepthChoiceGenerator(adja.size(), -1);
    int[] comb2;
    while ((comb2 = cg1.next()) != null) {
        if (Thread.currentThread().isInterrupted()) {
            break;
        }
        List<Node> s = GraphUtils.asList(comb2, adja);
        independenceTest.isIndependent(a, c, s);
        double _score = independenceTest.getScore();
        if (_score < score) {
            score = _score;
            S = s;
        }
    }
    DepthChoiceGenerator cg2 = new DepthChoiceGenerator(adjc.size(), -1);
    int[] comb3;
    while ((comb3 = cg2.next()) != null) {
        if (Thread.currentThread().isInterrupted()) {
            break;
        }
        List<Node> s = GraphUtils.asList(comb3, adjc);
        independenceTest.isIndependent(c, a, s);
        double _score = independenceTest.getScore();
        if (_score < score) {
            score = _score;
            S = s;
        }
    }
    // S actually has to be non-null here, but the compiler doesn't know that.
    if (S != null && !S.contains(b)) {
        scores.put(new Triple(a, b, c), score);
    }
}

Example 15 with DepthChoiceGenerator

use of edu.cmu.tetrad.util.DepthChoiceGenerator in project tetrad by cmu-phil.

the class Nlo method fullOrient6.

public Graph fullOrient6(Graph graph) {
    graph = GraphUtils.undirectedGraph(graph);
    graph = GraphUtils.replaceNodes(graph, dataSet.getVariables());
    Map<Node, List<Node>> cond = new HashMap<>();
    Map<Node, List<Double>> pVal = new HashMap<>();
    for (Node Y : graph.getNodes()) {
        System.out.println("Y = " + Y);
        List<Node> adjNodes = graph.getAdjacentNodes(Y);
        DepthChoiceGenerator gen = new DepthChoiceGenerator(adjNodes.size(), 4);
        int[] choice;
        List<Node> bestParents = null;
        while ((choice = gen.next()) != null) {
            List<Node> W = GraphUtils.asList(choice, adjNodes);
            double[] r = cci.residuals(name(Y), names(W));
            boolean indep = testIndependence(W, r);
            System.out.println("\tW = " + W + " indep = " + (indep) + " p = " + q);
            if (indep) {
                bestParents = W;
            }
        }
        cond.put(Y, bestParents);
    }
    for (Node Y : graph.getNodes()) {
        System.out.println("Y = " + Y + " cont = " + cond.get(Y));
        for (Node X : cond.get(Y)) {
            System.out.println("\tcond " + X + " = " + cond.get(X));
            if (!cond.get(X).contains(Y)) {
                graph.setEndpoint(X, Y, Endpoint.ARROW);
            }
        }
    }
    return graph;
}